Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | GPT-6 Luna Progpt-6-luna-pro | Gemma 4 31Bgemma-4-31b-it |
|---|---|---|
| Pricing | ||
| Input | $0.10 / 1M | $0.14 / 1M |
| Output | $0.50 / 1M | $0.40 / 1M |
| Cache Write (5m) | $0.10 / 1M | $0.14 / 1M |
| Cache Write (1h) | $0.10 / 1M | $0.14 / 1M |
| Cache Read | $0.10 / 1M | $0.14 / 1M |
| Web Search | $0 / 1M | $0 / 1M |
| Context | ||
| Max context | 1.1M | 262.1K |
| Max output | N/A | N/A |
| Capabilities | ||
| Vision | Yes | Yes |
| Function Calling | Yes | Yes |
| JSON Mode | Yes | Yes |
| Streaming | Yes | Yes |
| Catalogue | ||
| Provider | OpenAI | |
| Category | chat | chat |
| Charge type | Pay As You Go | Pay As You Go |
| Released | — | — |
| Description | ||
| Summary | GPT-6 Luna Pro uses the same underlying model as GPT-6 Luna, but runs with reasoning.mode set to pro for higher-quality responses on complex tasks. It combines Luna's speed and cost efficiency with deeper reasoning and more reliable multi-step execution, making it well suited for advanced coding, computer use, and agentic workflows where higher solution quality is needed without moving to a larger GPT-6 tier. | Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model, supporting text and image inputs with text outputs. It features a 256K token context window, configurable thinking/reasoning modes, native function calling, and broad multilingual support across 140+ languages. The model delivers strong performance in coding, reasoning, and document understanding, making it well suited for developer workflows, multilingual applications, and structured knowledge tasks. |